• Journal of Sensor Science and Technology
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• v.23 no.4
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• pp.251-258
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• 2014

While the feasibility of vertical velocity as a threshold parameter for pre-impact fall detection has been verified, effects of sensor attachment locations and methods calculating vertical acceleration and velocity on the detection performance have not been studied yet. Regarding the vertical velocity-based pre-impact fall detection, this paper investigates detection accuracies of eight different cases depending on sensor locations (waist vs. sternum), vertical accelerations (accurate acceleration based on both accelerometer and gyroscope vs. approximated acceleration based on only accelerometer), and vertical velocities (velocity with attenuation vs. velocity difference). Test results show that the selection of waist-attached sensor, accurate acceleration, and velocity with attenuation based on accelerometer and gyroscope signals is the best in overall in terms of sensitivity and specificity of the detection as well as lead time.

• Physical Therapy Rehabilitation Science
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• v.11 no.3
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• pp.311-320
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• 2022

Objective: To investigate the reliability and validity of static balance measurements using an acceleration sensor and a gyroscope sensor in smart phone inertial sensors. Design: Equivalent control group pretest-posttest. Methods: Subjects were forty five healthy adults aged twenty to fifty-years-old who had no disease that could affect the experiment. After pre-test, all participants wore a waist band with smart phone, and conducted six static balance measurements on the force plate twice for 35 seconds each. To investigate the test-retest reliability of both smart phone inertial sensors, we compared the intra-correlation coefficient (ICC 3, 1) between primary and secondary measurements with the calculated root mean scale-total data. To determine the validity of the two sensors, it was measured simultaneously with force plate, and the comparision was done by Pearson's correlation. Results: The test-retest reliability showed excellent correlation for acceleration sensor, and it also showed excellent to good correlation for gyroscope sensor(p<0.05). The concurrent validity of smartphone inertial sensors showed a mostly poor to fair correlation for tandem-stance and one-leg-stance (p<0.05) and unacceptable correlation for the other postures (p>0.05). The gyroscope sensor showed a fair correlation for most of the RMS-Total data, and the other data also showed poor to fair correlation (p<0.05). Conclusions: The result indicates that both acceleration sensor and gyroscope sensor has good reliability, and that compared to force plate, acceleration sensor has unacceptable or poor correlation, and gyroscope sensor has mostly fair correlation.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1421-1429
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• 2017

Human activity recognition has been studied using various sensors and algorithms. Human activity recognition can be divided into sensor based and vision based on the method. In this paper, we proposed an activity recognition system using acceleration sensor and gyroscope sensor in smartphone among sensor based methods. We used Deep Belief Network (DBN), which is one of the most popular deep learning methods, to improve an accuracy of human activity recognition. DBN uses the entire input set as a common input. However, because of the characteristics of different time window depending on the type of human activity, the RBMs, which is a component of DBN, are configured hierarchically by combining them from different time windows. As a result of applying to real data, The proposed human activity recognition system showed stable precision.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.2
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• pp.179-185
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• 2015

Although an accelerometer is a sensor that measures acceleration, it cannot be used by itself to measure the acceleration when the orientation of the sensor changes. This paper introduces a Kalman filter for the estimation of a sensor acceleration based on a six-axis inertial sensor (i.e., a three-axis accelerometer and three-axis gyroscope). The novelty of the proposed Kalman filter lies in the fact that its state vector includes not only the tilt angle variable but also the sensor acceleration. Thus, the filter can explicitly estimate the latter with a high accuracy. The accuracy of acceleration estimates were validated experimentally under three different dynamic conditions, using an optical motion capture system. It could be concluded that the performance of the proposed Kalman filter was comparable to that of the state-of-the-art estimation algorithm employed by the Xsens MTw. The proposed algorithm may be more suitable than inertial/magnetic sensor-based algorithms for various applications adopting six-axis inertial sensors.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.592-595
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• 2004

This paper presents a study on the development of a multi-sensing inertial sensor with a single mechanical structure, which can be used both as a gyroscope and an accelerometer. The proposed MEMS gyro-accelerometer is designed to detect the angular rate and the acceleration at the same time using two separate detection circuits for one proof mass. In this study, the detection and signal processing circuit for an effective signal processing of different inertial measurements is designed, fabricated, and tested. The experimental results show that the performances of the gyro-accelerometer have resolutions of 1mg and 0.025deg/sec and nonlinearities of less than 0.5% for the accelerometer and the gyroscope, respectively, which are similar results with those of sensors with different structures and different detection circuits. The size of the sensor is reduced almost by 50% comparing with the sensors of separated proof mass.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.741-744
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• 2009

In this paper, We introduce the glove mouse using a Gyroscope, acceleration sensor, Pin-type Viboratctile Display Device and USB HID. The device recognize a user's wrist by Gyroscope and acceleration sensor in the glove and transmit the data to USB dongle which is recognized the manufactured mouse by Blutooth. Also, using a special application, We transmit the tactile information to user through the Pin-type Vibrotactile Display. We implement wearable system in the glove except USB device. If user want to use general spatial mouse, we recognize mouse USB dongle only without another application. If user want to feel the tactile sensationn, we can use by connecting PC serial communication port to USB dongle.

• Journal of Applied Reliability
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• v.3 no.2
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• pp.103-116
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• 2003

We carry out reliability tests and investigate the failure mechanisms. of the wafer level vacuum packaged MEMS gyroscope sensor using an accelerated degradation test. The accelerated degradation test (ADT) is used to evaluate reliability (and/or life) of the MEMS vacuum package and to select the accelerated test conditions, which reduce the reliability testing time. Using the failure distribution model and stress-life model, we are able to estimate the average life time of the vacuum package, which is well agreed with the measured data. After improving several package reliability issues such as prevention of gas diffusion through package, we carry out another set of accelerated tests at the chosen acceleration level. The results show that reliability of the vacuum packaged gyroscope has been greatly improved and can survive without degradation of performance, which is the Q-factor in gyroscope sensor, during environmental stress reliability tests.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.5
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• pp.87-95
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• 2010

Lots of bridge structure generated the change of outward formation according to durability capability and decrepitude by long use. Especially, in case of the typhoon, snowing and earthquake is going to make rapidly more worse formation about the old structural facilitys. Also, outward formation by irregular and micro-distortion in bridge structure could not easily checked by normal diagnostics method. As a result, performance-capability of structure facility is getting to make a decline in standard of structure performance. Recently, real-time monitoring technology by wireless environment go into the study of irregular movement for structure facility. This paper presents the development of sensor to displacement checking about bridge structure. Sensing method of developed sensor put bring into the gyroscope technology using the acceleration speed and angular acceleration speed. This paper also will simulated to verified the monitoring capability of developed sensor against random vibration, frequency and distortion in simulated equipment.

• Journal of the Semiconductor & Display Technology
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• v.9 no.2
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• pp.41-47
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• 2010

In this paper we suggest an improvement upon the previous method of estimating a body's attitude. This paper presents a method that overcomes the shortcomings of previous studies. Applying the method of separating the acceleration of gravity component from the accelerometer's output improves the performance of the attitude estimation and extends the scope. In order to apply the method of the attitude estimation in an actively moving body, a new acceleration value containing the acceleration of gravity is calculated. This paper also proposes the method which minimizes the estimation error in estimating the moving body's attitude which is changing rapidly. Finally, this paper suggests a method that detects the gyroscope's drift and compensates for this drift using accelerometer. Applying the method improves the performance of the attitude estimation.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.297-310
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• 2022

Road facilities such as CCTV poles have potential risk of collision accidents with a car. A collision detection algorithm installed in the facility allows the collision accident to be known remotely. Most collision detection algorithms are operated by simply focusing on whether a collision have occurred, because these methods are used to measure only acceleration data from a 3-axis sensor to detect collision. However, it is difficult to detect other detailed information such as malfunction of the sensor, collision direction and collision strength, because it is not known without witness the accident. Therefore, we proposed enhanced detection algorithm to get the collision direction, and the collision strength from the tilt of the facility after accident using a 9-axis sensor in this paper. In order to confirm the performance of the algorithm, an accuracy evaluation experiment was conducted according to the data measurement cycle and the invocation cycle to an detection algorithm. As a result, the proposed enhanced algorithm confirmed 100% accuracy for 50 weak collisions and 50 strong collisions at the 9-axis data measurement cycle of 10ms and the invocation cycle of 1,000ms. In conclusion, the algorithm proposed is expected to provide more reliable and detailed information than existing algorithm.